Automated University-Community Partnership Matching System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
University-community partnerships face challenges in identifying potential partners with similar interests, as current methods rely heavily on manual searches and personal networks, which are time-consuming, labor-intensive, and may exacerbate bias or power relations.
Innovation Solution
A computer-implemented system that uses data organization methods, natural language processing, and semantic network analysis to facilitate collaboration between research entities by identifying shared topics of interest and providing a user interface for searching and communicating potential partnerships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual searches and personal networks are used to identify potential partners, then partnerships can be formed, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual mechanical searching processes with an automated computer-implemented system that uses data organization methods, natural language processing, and semantic network analysis to automatically identify potential partnership opportunities between university researchers and community organizations based on shared interests and topics
Solution Approach 2:
The system enables automatic identification and matching of potential partners through algorithmic processing of organizational data, eliminating the need for manual intervention in the initial partner identification phase while maintaining the ability for users to review and initiate connections
2Productivity
If manual searches are used to identify potential partners, then partnerships can be formed, but the process becomes labor-intensive
Solution Approach 1:
The patent substitutes manual labor-intensive searching with an automated computational system that processes organizational data, extracts interests and topics using natural language processing, and generates potential partnership matches without requiring manual reading and analysis of organizational profiles
Solution Approach 2:
The system introduces an intermediary automated matching platform that bridges university researchers and community organizations by algorithmically identifying shared interests and facilitating connections, reducing the direct manual effort required from users
3Adaptability or versatility
If personal networks are relied upon for partnership connections, then existing relationships can be leveraged, but the extent of relationships brokered is limited and bias or power relations may be exacerbated
Solution Approach 1:
The patent creates a universal matching system that can identify partnership opportunities across diverse organizations and researchers regardless of existing personal networks, using standardized data organization and analysis methods to discover connections that would otherwise remain unrecognized
Solution Approach 2:
The automated system serves as an impartial intermediary that objectively identifies potential partnerships based on shared interests and topics rather than personal connections, reducing bias and expanding the range of opportunities beyond existing networks
Data Source
AI summary
A system and associated methods apply text and network analysis methods to process information from online university researcher profiles and community organization websites to identify topics and shared interests that the groups have in common. The system includes a search platform that enables users to enter their name, their organization name, or a research topic and identify entities with similar work topics of interest. The system packages entity information and shared topic information into edge lists for ease of recall, and facilitates communication between entities.